Invited talk at Techcon #2 in Ramallah, titled: The Next Generation of the Web 3.0 - The Semantic Web

1. TechCon#2 – Developer Day
Ankars Suites, Ramallah, Palestine
October 12, 2032
The Next Generation of the Web 3.0
The Semantic Web
Dr. Mustafa Jarrar
Sina Institute, University of Birzeit
mjarrar@birzeit.edu
www.jarrar.info
Jarrar © 2013
1

2. What/why The Semantic Web, in short
The RDFa scenario
find a developer position, max 10 minutes from Ramallah
Jarrar © 2013
2

3. What/why The Semantic Web, in short
The RDFa scenario
Bad results, as it is
string-matching search,
i.e., not meaningful
search
find a developer position, max 10 minutes from Ramallah
Jarrar © 2013
3

4. What/why The Semantic Web, in short
The RDFa scenario
Shared meanings of things,
This meaning is embedded
inside web pages.

1
Ontology
2
―The semantic web‖ mission:
syntax to semantic based
search  The next generation
of the web.
3
4
find a developer position, max 10 minutes from Ramallah
3 billion pages
Jarrar © 2013
4

5. Let’s go back
Jarrar © 2013
5

6. From Web 1.0 to Web 2.0
Social Community, Collaboration, Sharing
Jarrar © 2013
6

7. Where Web 2.0 is going?
most Web 2.0 sites provide APIs
Jarrar © 2013
7

8. Wikipedia edited in real-time by anyone
(in 252 languages, millions of articles) written collaboratively
by volunteers around the world.
API
Jarrar © 2013
8

9. A social network for sharing photos
•3,464 uploads in the last minute ·
•160,129 things tagged with morning ·
•2.3 million things geotagged this month
In 2008
API
Jarrar © 2013
9

10. Upload, View, and Share Videos (and tags...)
API
Jarrar © 2013
10

11. e-Buy and e-Sell
Millions of items are listed, bought, sold, and discussed daily.
API
Jarrar © 2013
11

12. We know this! What is social?
API
Jarrar © 2013
12

13. Upcoimg.org
A social event calendar website, uses iCalender, supports an open API
for the submission of event descriptions.
API
Jarrar © 2013
13

14. Blog (Your Own Journal)
Commentary, news, personal diaries... + comments/discussions
(+106 million blogs, as of 2007)
API
Jarrar © 2013
14

15. Business/Professional Networking
16 million registered users (2007)
60 million registered users (2007)
Social employability
API
Jarrar © 2013
15

16. Social Networking
Find your friends, socialize, group, share/organize events, and
more…(55 million active members)
API
Jarrar © 2013
16

17. Web 2.0 Technologies
Companies are competing in gathering content from people
and
offering this content back through APIs (i.e. structured data)
Content syndication
How can you deliver recent news to your users without forcing
them to visit your website?  RSS, Atom
Mashups
How can you remix free content and make a new website?
Web APIs (programmable web)
How can make use of the free content inside my website?
Jarrar © 2013
17

18. Content Syndication
Millions of online publishers including newspapers, commercial web
sites and blogs now publish their latest news headlines, product offers
or blog postings in standard format news feed.
A typical web
feed logo
Jarrar © 2013
18

19. Content Syndication
The two main families of web syndication formats are RSS and Atom.
Jarrar © 2013
19

20. Mashups / Programmable Web
(The Puzzle of APIs)
Jarrar © 2013
20

21. Mashups
• A new type of web applications.
• Combines data from more than one source into a single integrated
tool.
• Creating a new and distinct web service that was not originally
provided by either source.
• Content is typically sourced via an API* or a RSS Feed
Let’s see some examples..
Jarrar © 2013
21

22. Mashups (Example)
Ask500People.com
Real-time mashup of votes from around the world
Jarrar © 2013
22

23. Mashups (Example)
ePartyGuide.com
Yahoo! MapsYahoo! LocalFlickr-
Jarrar © 2013
23

24. Mashups (Example)
Combines Google maps with real-estate databases
Google MapsReal-estate-
Jarrar © 2013
24

25. Mashups (Example)
A unified and comprehensive view of the current global state of
infectious diseases and their effect on human and animal health
Google NewsProMEDWorld Health
OrganizationJarrar © 2013
25

26. Mashups (Example)
A visually rich application that combines the Amazon API to show the
relationship between movies, bands, actors, etc.
Amazon APIYou TubeOthersJarrar © 2013
26

27. Be Innovative… (The Puzzle of APIs)
Jarrar © 2013
27

28. Find popular APIs
Jarrar © 2013
28

29. Find popular APIs here
Also, How-To start a
mashup
Jarrar © 2013
29

30. (APIX + APIY = Money)
… Be innovative to know x and y ;-)
See the ―Mashup Market‖
Jarrar © 2013
30

31. The Mashup Phenomena
 From Web of Documents (Hypertext) into Web of Data
In other words,
The Web is becoming a Database, where
a data source is seen as a table, and
a mashup is seen a query over multiple tables/sources.
 Data Web

32. Web 2.0 challenges
Suppose you want to build a mashup:
Build up your publications “publications webpage”, combining all
data from all sources/APIs?
• How to link data items cross sources?
• How to answer structured queries (over different APIs)
such as ―Give me all people who works-at Birzeit and previously
lived in Belgium‖?
• How to know the meaning/type of data Items? Bessan is
a person name, or a city name?
 Linking data items cross sources, such that it becomes
easy to integrate search, and retrieve (use RDF).
Jarrar © 2013
32

33. From Web 2.0 to Web 3.0
The four principles of Linked Data -Tim Berners-Lee
1. Use URIs to denote things.
2. Use HTTP URIs so that these things can be referred to and looked
up ("dereferenced") by people and user agents.
3. Provide useful information about the thing when its URI is
dereferenced, leveraging standards such as RDF, SPARQL.
4. Include links to other related things (using their URIs) when
publishing data on the Web.
Jarrar © 2013
33

34. Linked Data
• A community project to publish various open datasets as RDF on the Web
and by setting RDF links between data items from different data sources.
• Data items are linked across datasets (Palestine in DBPedia is the same
Palestine in Yago, in Fliker, YouTube, ….)
• By Sep 2011 this had grown to 39 billion RDF triples.
Jarrar © 2013
34

35. Linking Data
•
•
•
How are same entities described in different datasets linked?
AGAIN: By linking the Global Identifier, that is, the URI!
Let’s have a look at real examples from real datasets:
<http://dbpedia.org/resource/Bethlehem> owl:sameAs
<http://sws.geonames.org/284315/>
• Linking the entity ―Bethlehem‖ between the DBPedia dataset and the Geonames dataset
in the Linking Open Data cloud.
• This is done by linking the URIs of ―Bethlehem‖ in both datasets using owl:sameAs.
<http://dbpedia.org/resource/Tim_Berners-Lee> owl:sameAs
<http://www4.wiwiss.fu-berlin.de/dblp/resource/person/100007>
• Linking the entity ―Tim Berners-Lee‖ between the DBPedia dataset and the DBLP dataset .
• This is done by linking the URIs of ―Tim Berners-Lee‖ in both datasets using owl:sameAs.
Jarrar © 2013
35

36. Resources
 http://dbpedia.org/resource/Bethlehem
(Bethlehem URI in DBPedia)
http://sws.geonames.org/284315/ 
(Bethlehem URI in Geonames)
Jarrar © 2013
36

37. There are many ways to
consume such data
Among them is
RDFa
(Resource Description Framework in Attributes)
W3C Recommendation, in 2008
Jarrar © 2013
37

38. RDFa
• Bridges the gap between the Web of Documents and the
Web of Data (Web 3.0).
• Makes XHTML web pages structured data (by embedding
RDF triples inside XHTML).
• i.e., using RDFa we build small RDF graphs and embed them
inside XHTML pages.
Jarrar © 2013
38

39. RDFa
• As stated by Google Webmasters guide, RDFa can be roughly viewed
as a way to label content to describe a specific type of information,
such as a restaurant review, an event, a person, or a product listing.
• These information types are called entities or items. Each entity has
a number of properties. For example, a Person has the properties
name, address, job title, company, and email address.
• In general, RDFa uses simple attributes in XHTML tags (often <span>
or <div>) to assign brief and descriptive names to entities and
properties.
Jarrar © 2013
39

40. Example 1
Jarrar © 2013
40

41. Example 1
Jarrar © 2013
41

42. Example 2
Consider this HTML block:
<div>
My name is George Mousa. My friends call me Geno. I live in
Nablus, Palestine. I work as an engineer at Birzeit
University.
</div>
Annotate the HTML block above with RDFa:
<div xmlns:v="http://rdf.data-vocabulary.org/#"
typeof="v:Person">
My name is <span property="v:name"> George Mousa </span>.
My friends call me <span property="v:nickname"> Geno </span>.
I live in Nablus, Palestine.
I work as an engineer at <span property="v:affiliation">
Birzeit University </span>.
</div>
Jarrar © 2013
42

43. Example 2
<div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Person">
My name is <span property="v:name"> George Mousa </span>.
My friends call me <span property="v:nickname"> Geno </span>.
I live in Nablus, Palestine.
I work as an engineer at <span property="v:affiliation"> Birzeit University
</span>. </div>
• The example begins with a namespace declaration using xmlns. This
indicates the namespace where the vocabulary is specified.
• Also on the first line, typeof="v:Person" indicates that the markedup content represents a Person.
• Each property of the person (such as the name and nickname) is
labeled using property.
• To indicate a URL, use rel instead of property. Consider adding
the following to our example inside the Person DIV
My home page is: <a href="http://www.example.com"
rel="v:url">www.example.com</a>.
•
"rel" is used to convey the relationship between two entities—in this case, a
Person entity and a webpage entity.
Jarrar © 2013
43

44. Example 2
•
In our example, we have addressing information about George Mousa.
<div>
•
•
•
... I live in Nablus, Palestine. I work as an engineer ... </div>
We use nesting. Nesting is when one information type includes the other.
In this case, we want to include George’s Address information
(typeof="v:Address") in the typeof="v:Person“ entity.
Here, we use rel to indicate a relationship between George (the entity v:Person)
and his address (the entity v:Address).
<div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Person">
My name is <span property="v:name"> George Mousa </span>.
My friends call me <span property="v:nickname"> Geno </span>.
I live in
<span rel="v:Address">
<span typeof="v:Address">
<span property="v:city">Nablus</span>,
<span property="v:country">Palestine</span>
</span>
</span>.
I work as an engineer at <span property="v:affiliation"> Birzeit University
</span>.
Jarrar © 2013
44
</div>

45. Let’s draw a graph of our example!
v:Person
“George Mousa”
v:nickname
“Geno”
v:Address
v:city
“Nablus”
“Palestine”
“Birzeit University”
Jarrar © 2013
45

46. Jobs.ps Use Case
Page 1
Page n
Jarrar © 2013
46

47. RDF (short tutorial)
Let’s go a little deeper to know how RDF
represents data.
Jarrar © 2013
47

48. Recall XML
<address>
<name>Universsity of Birzeit</name>
<street>Almarj 435</street>
<town>Birzeit</town>
</address>
Jarrar © 2013
48

49. Recall XML
XML Markup 1:
<address>
<name>University of Birzeit</name>
<street>Almarj 435</street>
<town>Birzeit</town>
</address>
XML stylesheets
are
also usable to transform
XML representations
XML Markup 2:
<address>
<name>University of Birzeit</name>
<place>
<street>Almarj 435</street>
<town>Birzeit</town>
</place>
</address>
Jarrar © 2013
49

50. Why XML is Not Enough
• It provides syntax, but not semantics, which is important when
exchanging/representing data over the Web.
<aaaa>
<bbbb>Universsity of Birzeit</aaaa>
<cccc>Almarj 435</cccc>
<dddd>Birzeit</dddd>
</aaaa>
• Not primitive. Same data can be represented in many ways, which is a
problem when exchanging/representing data over the Web.
<address>
<name>University of Birzeit</name>
<street>Almarj 435</street>
<town>Birzeit</town>
</address>
<address name=―University of Birzeit‖>
<street>Almarj 435</street>
<town>Birzeit</town>
</address>
Jarrar © 2013
50

51. What is RDF?
• It is used for describing resources on the web.
• Makes use of URIs to identify web resources and is
written in XML.
• It is not a language but a framework
• You see it as a way of writing XML  making it meaningful and more
primitive.
• You may see it independent, RDF data might never occur in XML form
• W3C standard
Jarrar © 2013
51

52. What is RDF?
Data is represented in RDF as a directed labeled graph.
An RDF graph is a set of triples, of the form <Subject, Predicate, Object>
Each Subject and each Predicate must be a URI; that is, it has to be a
unique identifier, not a literal. An Object can be either a URI or a literal.
Jarrar © 2013
52

53. Example
http://www.amazon.com/Orientalism-Edward-W-Said/dp/039474067Xc
11$
:WrittenBy
Edward Said
Orientalism
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-ns#
xmlns:a="http://www.example.com"
xmlns:w="http://en.wikipedia.org/wiki/">
<rdf:Description rdf:about="http://www.amazon.com/Orientalism-Edward-W-Said/dp/039474067X">
<a:Title>Orientalism</a:Title>
<a:Price>11$</a:Price>
<a:Author>Edward_Said</a:Author>
</rdf:Description>
</rdf:RDF>
Jarrar © 2013
53

54. Example
a:Author
http://en.wikipedia.org/wiki/Edward_Said
25/9/2003
11$
Orientalism
1/11/1935
a:BirthCity
http://www.amazon.com/Orientalism-Edward-W-Said/dp/039474067Xc
Edward Saïd
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-ns#
Jerusalem
xmlns:a="http://www.example.com/"
xmlns:w="http://en.wikipedia.org/wiki/">
<rdf:Description rdf:about="http://www.amazon.com/Orientalism-Edward-W-Said/dp/039474067X">
<a:Title>Orientalism</a:Title>
<a:Price>11$</a:Price>
<a:Author>
<rdf:Description rdf:about="w:Edward_Said">
<a:BirthCity>Jerusalem</a:BirthCity>
<a:BornAt>1/11/1935</a:BornAt>
<a:DiedA>25/9/2003</a:DiedA>
</rdf:Description>
</a:Author>
</rdf:Description>
</rdf:RDF>
<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
Jarrar © 2013
54

55. Example
:Author
25/9/2003
http://en.wikipedia.org/wiki/Edward_Said
:BirthCity
http://www.amazon.com/Orientalism-Edward-W-Said/dp/039474067Xc
<?xml version="1.0"?>
Orientalism
Edward
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
11$
1/11/1935
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:a="http://www.example.com#"
xmlns:w="http://en.wikipedia.org/wiki/">
http://en.wikipedia.org/wiki/Jerusalem
<rdf:Description rdf:about="http://www.amazon.com/Orientalism-Edward-W-Said/dp/039474067X">
<a:Title>Orientalism</a:Title>
<a:Price>11$</a:Price>
<a:Author>
<rdf:Description rdf:about="w:Edward_Said">
<a:BornAt>1/11/1935</a:BornAt>
<a:DiedA>25/9/2003</a:DiedA>
760800
Palestine
<a:BirthCity>
<rdf:Description rdf:about="http://en.wikipedia.org/wiki/Jerusalem">
<a:Population>760800</a:Population>
<a:CapitalOf>Palestine</a:CapitalOf>
</rdf:Description>
</a:BirthCity>
</rdf:Description>
</a:Author>
</rdf:Description>
</rdf:RDF>
Jarrar © 2013
Saïd
55

56. Some slides borrowed from Mohammad A. ZeinEddin
Facebook Open Graph
Jarrar © 2013
56

57. Definitions
•
Social Web: relations between people and people… people and
objects.
•
Social graph: a graph that represents the social web…
•
Open Graph protocol: a way to transform any regular webpage to a
rich object in a social graph.
•
Facebook open graph: a way to integrate a transformed (an object)
webpage into facebook.
Jarrar © 2013
57

58. How to transform a webpage to be a part of
the Open Graph
•
Add the Open Graph schema (http://ogp.me/ns#) to the
webpage html tag.
•
Add some meta data properties to your webpage. The
minimum needed are:
–
–
type
–
url
–
•
title
Image
Now the webpage is an Open Graph object.
Jarrar © 2013
58

59. How to transform a webpage to an object
A regular employee webpage:
<html>
<head>
<title>Mohammad ZeinEddin</title>
</head>
<body>
The employee webpage
</body>
</html>
A “minimal” facebook open graph object for the previous webpage:
<html xmlns:og="http://ogp.me/ns#">
<head>
<title>Mohammad ZeinEddin </title>
<meta property="og:title" content=“Mohammad ZeinEddin"/>
<meta property="og:type" content=" public_figure"/>
<meta property="og:url" content="http://www.birzeit.edu/employees/mohammad.zeineddin"/>
<meta property="og:image" content="https://ritaj.birzeit.edu/profile/photo?person_id_v=45761&attche_type=PIC"/>
</head>
<body>
The employee webpage
</body>
</html>
Jarrar © 2013
59

60. One page  One object
•
Note that the webpage can represent only one object.
•
The Object can be anything.
•
Facebook has some predefined object types like activity,
sport, company, restaurant, cause, university, city, game
and many others… (Facebook Open Graph)
•
You can define any object type within your own schema.
Jarrar © 2013
60

61. Our Employee webpage is now an object
OBJECT
EMPLOYEE
Jarrar © 2013
61

62. Make a relation between a fecebook user
and the object
When a User RECOMMEND an Employee… a relation is
constructed…
User
Action
OBJECT
RECOMMEND
EMPLOYEE
Jarrar © 2013
62

63. Now it can be integrated into facebook
open graph
New
Relation
https://developers.facebook.com/docs/concepts/opengraph/
Jarrar © 2013
63

64. Users are connected through social objects
Are connected
through
https://developers.facebook.com/docs/concepts/opengraph/
Modified
Jarrar © 2013
64

65. Why Facebook choose Open Graph
• It is a minimal RDFa.
• Facebook needs one namespace and one prefix! They
didn’t like the following:
<html xmlns="http://www.w3.org/1999/xhtml"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:dc="http://purl.org/dc/elements/1.1/">
<meta property="dc:creator" content=―Mohammad ZeinEddin" />
<link rel="foaf:primaryTopic" href="http://example.org/john-d/#me" />
• Facebook reuse one html tag attribute:
<meta property="og:title" content=―Mohammad ZeinEddin"/>
Jarrar © 2013
65

66. Facebook Graph Search
FB? Oracle?
When can we Google the web in this way
Jarrar © 2013
66

67. Conclusion (Informally Speaking)
From Web of documents to Web of Objects
Jarrar © 2013
67

68. Related Research @Birzeit
Arabic Ontology
MashQL for (Query/mashing up web data)
Jarrar © 2013
68

69. MashQL
This research was initiated at the University of Cyprus
A language
for querying and Mashing up the Web 3.0
With the following assumptions in mind:
 The user does not know the schema.
 There is no offline or inline schemaontology.
 The query may involve multiple sources.
 an expressive language. (not a single-purpose interface)
Jarrar © 2013
69

70. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Author ―^Lara‖
YearPubYear > 2007
Title
ArticleTitle
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
 Interactive Query Formulation.
 MashQL queries are translated into and executed as SPARQL.
Jarrar © 2013
70

71. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Jarrar © 2013
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
71

72. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Everything
Article
A1
A2
B1
Types Individuals
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
Background queries
SELECT X WHERE {?X ?P ?O}
Union
SELECT X WHERE {?S ?P ?X}
SELECT X WHERE {?S rdf:Type ?X}
Jarrar © 2013
72

73. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Author
Author
Title
PubYear
Type
Year
Contains Lara
Equals
Equals
Contains
Contains
OneOf
Not
Between
LessThan
MoreThan
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
Background query
SELECT P WHERE {?Everything ?P ?O}
Jarrar © 2013
73

74. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Author ―^Lara
Year PubYear
Author
Title
PubYear
Type
Year
MoreTh
2007
Equals
Equals
Contains
OneOf
Not
Between
LessThan
MoreThan
MoreThan
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
Background query
SELECT P WHERE {?Everything ?P ?O}
Jarrar © 2013
74

75. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Author ―^Lara
YearPubYear > 2007
Title
Author
Author
Title
Title
PubYear
Type
Year
ArticleTitle
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
Background query
SELECT P WHERE {?Everything ?P ?O}
Jarrar © 2013
75

76. Example 1
“Lara’s articles after 2007?”
RDF Input
From:
http://www.site1.com/rdf
www.site1.com/rdf
:B1
:B1
:B1
:B1
:B2
:B2
:Title “Linked Data”
:Author “Lara T.”
:PubYear 2008
:Publisher “Springer”
:Title “Data on the Web”
:Author “Abiteboul S.”
http://www.site2.com/rdf
www.site2.com/rdf
:A1
:A1
:A1
:A1
:A1
:A2
:A2
:A2
:A2
Query
Everything
Author ―^Lara
YearPubYear > 2007
Title
ArticleTitle
rdf:Type bibo:Article
:Title “Data Web”
:Author “Tom Lara”
:Author “Bob Hacker”
:Year
2007
rdf:Type bibo:Article
:Title “Semantic Web”
:Author “Tom Lara”
:Year
2005
PREFIX S1: <http://site1.com/rdf>
PREFIX S2: <http://site1.com/rdf>
SELECT ?ArticleTitle
FROM <http://site1.com/rdf>
FROM <http://site2.com/rdf>
WHERE {
{?X S1:Author ?X1} UNION {?X S2:Author ?X1}
{?X S1:PubYear ?X2} UNION {?X S2:Year ?X2}
{{?X S1:Title ?ArticleTitle} UNION {?X S2:Title
?ArticleTitle}}
FILTER regex(?X1, “^Hacker”)
JarrarFILTER (?X2
© 2013
> 2000)}
76

77. Example 2
“Recent articles from Cyprus?”
Query
Article
Title ArticleTitle
Author
Address
Country ―Cyprus‖
Year > 2008
 Retrieve every Article that: has a title, written by author, who has
address, this address has a country called Cyprus, and the article is
published after 2008.
Jarrar © 2013
77

78. MashQL Editor






Alpha version (Not public YET!)
Web Ajax-based.
Open sources Java Script libraries (from Yahoo)
Oracle 11g as RDF store.
Graphs Signature Index for fast user-interaction.
URI Normalization based on heuristics.
(but some URIs are too cryptic)
Jarrar © 2013
78

79. MashQL Firefox Add-On (Light-mashups @ your browser)
The browser becomes a web composer (not only a navigator )
Jarrar © 2013
79

80. Evaluation (DBLP, Experiment 1)
(User Interaction Response Time)
How long it takes to generate the next list?
Query
Any Article
 O:(?S Type ?O)


Title
―^World-Wide Web‖

Creator
Type
Name
Year
Query
Q1
Q2
Q3
Q4

Person


―^Berners-Lee‖

 P:(?S Type Article)(?S ?P ?O1)
 P:(?S Type Article)
(?S Creator ?O1) (?O1 ?P ?O2)
 O:(?S Type Article)
(?S Creator ?O1)(?O1 Type ?O)
> 2007
DBLP (9M triples)
GS
Oracle
0.003
0.001
0.001
0.001
0.005
0.136
0.187
1.208
DBLP (4M triples)
GS
Oracle
0.003
0.001
0.001
0.001
Jarrar © 2013
0.004
0.148
0.846
0.835
DBLP (2M triples)
GS
Oracle
0.003
0.001
0.001
0.001
0.003
0.108
0.671
0.650
80

81. Evaluation (DBPedia, Experiment 2)
 P:(?S :Type :Album)
(?S :PreviousAlbum ?O1)
(?O1 ?P ? O2)
Query
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
DBPedia (32 M)
0.003
0.002
0.005
0.005
0.005
0.005
0.007
0.005
0.007
DBPedia (16 M)
DBPedia (8 M)
0.003
0.003
0.002
0.002
0.004
0.003
0.004
0.004
0.004
0.004
0.005
0.005
0.007
0.007
0.005
0.005
0.007 © 2013
0.007
Jarrar
DBPedia (4 M)
0.003
0.002
0.003
0.004
0.004
0.005
0.007
0.005
0.006
81

82. Evaluation (DBPedia, Experiment 3)
 P3:(?S Type ?Album)
(?S ?RelatedTo1 ?O1)
(?O1 ?RelatedT02 ?O2)
(?O2 ?P3 ?O4)
Query
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
(B32) 32 M
GS
Oracle
0.001
0.027
0.026
17.450
0.048
49.656
0.087 5348.774
0.135
0.185
0.234
0.265
0.280
-
DBPedia (16 M )
0.001
0.010
0.010
0.022
0.036
0.055
0.076
0.098
Jarrar0.110
© 2013
DBPedia (8 M )
0.001
0.006
0.011
0.017
0.032
0.047
0.061
0.077
0.092
DBPedia (4 M )
0.001
0.005
0.010
0.011
0.011
0.016
0.023
0.027
0.034
82

83. Graph Signature (a native RDF Index)
• Summary of all paths.
• We query the Graph Signature instead of the Data Graph.
Jarrar © 2013
83

84. Conclusions
 ―Query and mash up the Data Web as simple as filtering up
Web Feeds‖ is a query formulation problem.
 End-users can navigate, query, and mash up unknown graphs.
without knowing the schema. Data is schema-free. Multiple sources.
 MashQL is expressive as SPARQL.
Except NAMED GRAPH.
 MashQL is not merely a SPARQL interface, or limited RDF.
It has its own path-pattern intuition (can be similarly used for XML and DB).
Jarrar © 2013
84

85. Thank You
Download the slides from www.jarrar.info
Reading:
Mustafa Jarrar and Marios D. Dikaiakos: A Data Mashup Language for the Data Web.
Proceedings of LDOW, WWW'09. ACM. ISSN 1613-0073. (2009).
http://www.jarrar.info/publications/JD09.pdf.htm
Mustafa Jarrar and Marios D. Dikaiakos: MashQL: A Query-by-Diagram Language Towards Semantic Data Mashups. Proceedings of ONISW'08, part of the ACM CiKM
conference. ACM. pages (89-96) ISBN 9781605582559. (2008).
http://www.jarrar.info/publications/onisw10-jarrar.pdf.htm
Jarrar © 2013
85